The spread of drug resistance of Plasmodium falciparum and Plasmodium vivax parasites is a challenge towards malaria elimination. P. falciparum has shown an early and severe drug resistance in comparison to P. vivax in various countries. In fact, P. vivax differs in its life cycle and treatment in various factors: development and duration of sexual parasite forms differ, symptoms severity are unequal, relapses present only in P. vivax cases and the Artemisinin-based combination therapy (ACT) is only mandatory in P. falciparum cases. We compared the spread of drug resistance for both species through two compartmental models using ordinary differential equations. The model structure describes how sensitive and resistant parasite strains infect a human population treated with antimalarials. We found that an early transmission,i.e., before treatment and low effectiveness of drug coverage, supports the prevalence of sensitive parasites delaying the emergence of resistant P. vivax. These results imply that earlier attention of both symptomatic cases and reservoirs of P. vivax are essential in controlling transmission but also accelerate the spread of drug resistance.

In current peer-to-peer applications content is generally static, i.e. it does not change over time. In the case of content that is modified over time, peers that host such dynamic content are required to have a mechanism that refreshes content hosted by them. In unstructured peer-to- peer networks this is challenging because of its decentralized nature. In this paper we develop a model that captures for dynamic content in a peer-to-peer network the impact of its refreshing rate and its popularity to the bandwidth required from the network. We compare four simple mechanisms for updating peers that can be used in a protocol devised to work in this kind of scenario. We find that there is an optimal number of updates to proactively push into the network in order to minimize the bandwidth consumption. Since unstructured peer-to-peer networks offer little guarantees of reliability, the use of one of the mechanisms studied here is highly recommended.

Server providers that support e-commerce applications as a service for multiple e-commerce Web sites traditionally use a tiered server architecture. This architecture includes an application tier to process requests for dynamically generated content. How this tier is provisioned can significantly impact a provider's profit margin. In this article we study methods to provision servers in the application serving tier that increase a server provider's profits. First, we examine actual traces of request arrivals to the application tier of an e-commerce site, and show that the arrival process is effectively Poisson. Next, we construct an optimization problem in the context of a set of application servers modeled as M / G /1/ PS queueing systems, and derive three simple methods that approximate the allocation that maximizes profits. Simulation results demonstrate that our approximation methods achieve profits that are close to optimal, and are significantly higher than those achieved via simple heuristics.

Demand for content served by a provider can fluctuate with time, complicating the task of provisioning serving resources so that requests for its content are not rejected. One way to address this problem is to have providers form a collective in which they pool together their serving resources to assist in servicing requests for one another's content. In this paper, we determine the conditions under which a provider's participation in a collective reduces the rejection rate of requests for its content - a property that is necessary for such a provider to justify its participation within the collective. We show that all request rejection rates are reduced when the collective is formed from a homogeneous set of providers, but that some rates can increase within heterogeneous sets. We also show that, asymptotically, growing the size of the collective will sometimes, but not always, resolve this problem. We explore the use of thresholding techniques, where each collective participant sets aside a portion of its serving resources to serve only requests for its own content. We show that thresholding allows a more diverse set of providers to benefit from the collective model, making collectives a more viable option for content delivery services.

Server providers that support e-commerce applications as a service to multiple e-commerce websites traditionally use a tiered server architecture. This architecture includes an application tier to process requests that require dynamically generated content. How this tier is provisioned can significantly impact a provider's profit margin. We study methods to provision servers in the application serving tier to increase a server provider's profits. First, we examine actual traces of request arrivals to the application tier of e-commerce sites, and show that the arrival process is effectively Poisson. Next, we construct an optimization problem in the context of a set of application servers modeled as M/G/l/PS queueing systems, and derive three simple methods to approximate the allocation that maximizes profits. Simulation results demonstrate that our approximation methods achieve profits that are close to optimal and are significantly higher than those achieved via simple heuristics.